Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI 02912, USA.
Proc Biol Sci. 2022 Mar 9;289(1970):20212089. doi: 10.1098/rspb.2021.2089. Epub 2022 Mar 2.
Patterns of collective motion in bird flocks, fish schools and human crowds are believed to emerge from local interactions between individuals. Most 'flocking' models attribute these local interactions to hypothetical rules or metaphorical forces and assume an omniscient third-person view of the positions and velocities of all individuals in space. We develop a of collective motion in human crowds based on the visual coupling that governs pedestrian interactions from a first-person embedded viewpoint. Specifically, humans control their walking speed and direction by cancelling the average angular velocity and optical expansion/contraction of their neighbours, weighted by visibility (1 - occlusion). We test the model by simulating data from experiments with virtual crowds and real human 'swarms'. The visual model outperforms our previous omniscient model and explains basic properties of interaction: 'repulsion' forces reduce to cancelling optical expansion, 'attraction' forces to cancelling optical contraction and 'alignment' to cancelling the combination of expansion/contraction and angular velocity. Moreover, the neighbourhood of interaction follows from Euclid's Law of perspective and the geometry of occlusion. We conclude that the local interactions underlying human flocking are a natural consequence of the laws of optics. Similar perceptual principles may apply to collective motion in other species.
鸟类群体、鱼类群体和人群的集体运动模式被认为是个体之间局部相互作用的结果。大多数“群体”模型将这些局部相互作用归因于假设的规则或隐喻的力量,并假设对空间中所有个体的位置和速度具有全知的第三人称视角。我们从嵌入的第一人称视角出发,基于视觉耦合,开发了一种人类群体的集体运动模型。具体来说,人类通过取消邻居的平均角速度和光的膨胀/收缩(通过可见度 1-遮挡进行加权)来控制行走速度和方向。我们通过模拟虚拟人群和真实人类“蜂群”的实验数据来测试模型。视觉模型优于我们之前的全知模型,并解释了相互作用的基本特性:排斥力可简化为取消光的膨胀,吸引力可简化为取消光的收缩,对齐可简化为取消膨胀/收缩和角速度的组合。此外,相互作用的邻域遵循欧几里得的透视定律和遮挡的几何形状。我们的结论是,人类群体中潜在的局部相互作用是光学定律的自然结果。类似的感知原则可能适用于其他物种的集体运动。